2019/01/23 by Pedro A. Gómez, Miguel Molina‐Romero, Gómez, Pedro A. +9
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · Medicine · #Advanced MRI Techniques and Applications #FOS: Electrical engineering #Generative Adversarial Networks and Image Synthesis #Image and Video Processing (eess.IV) #Single-cell and spatial transcriptomics #eess.IV #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1901.07800
arxiv created 2019/01/23 · openalex publication_date 2019/01/23 · arxiv updated 2019/01/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Magnetic resonance imaging (MRI) is a remarkably powerful diagnostic technique: it generates wide-ranging information for the non-invasive study of tissue anatomy and physiology. Complementary data is normally obtained in separate measurements, either as contrast-weighted images, which are fast and simple to acquire, or as quantitative parametric maps, which offer an absolute quantification of underlying biophysical effects, such as relaxation times or flow. Here, we demonstrate how to acquire and reconstruct data in a transient-state with a dual purpose: 1 - to generate contrast-weighted images that can be adjusted to emphasise clinically relevant image biomarkers; exemplified with signal modulation according to flow to obtain angiography information, and 2 - to simultaneously infer multiple quantitative parameters with a single, highly accelerated acquisition. This is a achieved by introducing three novel elements: a model that accounts for flowing blood, a method for sequence design that incorporates both parameter encoding and signal contrast, and the reconstruction of temporally resolved contrast-weighted images. From these images we simultaneously obtain angiography projections and multiple quantitative maps. By doing so, we increase the amount of clinically relevant data without adding measurement time, creating new dimensions for biomarker exploration and adding value to MR examinations for patients and clinicians alike.